Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands
<p>Recent years have seen a rapid surge in the use of light detection and ranging (lidar) technology for characterizing the structure of ecosystems. Even though repeated airborne laser scanning (ALS) surveys are becoming increasingly available across several European countries, so far, only a...
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Copernicus Publications
2025-07-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/3641/2025/essd-17-3641-2025.pdf |
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| author | Y. Shi J. Wang W. D. Kissling |
| author_facet | Y. Shi J. Wang W. D. Kissling |
| author_sort | Y. Shi |
| collection | DOAJ |
| description | <p>Recent years have seen a rapid surge in the use of light detection and ranging (lidar) technology for characterizing the structure of ecosystems. Even though repeated airborne laser scanning (ALS) surveys are becoming increasingly available across several European countries, so far, only a few studies have derived data products of ecosystem structure at a national scale, possibly due to a lack of free and open-source tools and the computational challenges involved in handling the large volumes of data. Nevertheless, high-resolution data products of ecosystem structure generated from multi-temporal country-wide ALS datasets are urgently needed if we are to integrate such information into biodiversity and ecosystem science. By employing a recently developed, open-source, high-throughput workflow (named “Laserfarm”), we processed around 70 TB of raw point clouds collected from four national ALS surveys of the Netherlands (AHN1–AHN4, 1996–2022). This resulted in <span class="inline-formula">∼59</span> GB raster layers in GeoTIFF format constituting ready-to-use multi-temporal data products of ecosystem structure at a national scale. For each AHN (Actueel Hoogtebestand Nederland) dataset, we generated 25 lidar-derived vegetation metrics at 10 m spatial resolution, representing vegetation height, vegetation cover, and vegetation structural variability, together with auxiliary data (<span class="inline-formula">∼12</span> GB) such as raster layers of point density; pulse density; flight line timestamp information; terrain and surface elevation; and masks of water areas, roads, buildings, power lines, and NA values (areas with no points available). The data enable an in-depth understanding of ecosystem structure at a fine resolution across the Netherlands and provide opportunities for exploring ecosystem structural dynamics over time. To illustrate the utility of these data products, we present ecological use cases that monitor forest structural change and analyse vegetation structure differences across various Natura 2000 habitat types, including dunes, marshes, grasslands, shrublands, and woodlands. The provided data products and the employed workflow can facilitate a wide use and uptake of ecosystem structure information in biodiversity and carbon modelling, conservation science, and ecosystem management. The full data products are publicly available on Zenodo (<a href="https://doi.org/10.5281/zenodo.13940846">https://doi.org/10.5281/zenodo.13940846</a>, Shi et al., 2025a).</p> |
| format | Article |
| id | doaj-art-23ef439dd66d443794bcf0ea5260cc81 |
| institution | Kabale University |
| issn | 1866-3508 1866-3516 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
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| series | Earth System Science Data |
| spelling | doaj-art-23ef439dd66d443794bcf0ea5260cc812025-08-20T03:34:45ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162025-07-01173641367710.5194/essd-17-3641-2025Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the NetherlandsY. Shi0J. Wang1W. D. Kissling2Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94240, 1090 GE Amsterdam, the NetherlandsInstitute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94240, 1090 GE Amsterdam, the NetherlandsInstitute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94240, 1090 GE Amsterdam, the Netherlands<p>Recent years have seen a rapid surge in the use of light detection and ranging (lidar) technology for characterizing the structure of ecosystems. Even though repeated airborne laser scanning (ALS) surveys are becoming increasingly available across several European countries, so far, only a few studies have derived data products of ecosystem structure at a national scale, possibly due to a lack of free and open-source tools and the computational challenges involved in handling the large volumes of data. Nevertheless, high-resolution data products of ecosystem structure generated from multi-temporal country-wide ALS datasets are urgently needed if we are to integrate such information into biodiversity and ecosystem science. By employing a recently developed, open-source, high-throughput workflow (named “Laserfarm”), we processed around 70 TB of raw point clouds collected from four national ALS surveys of the Netherlands (AHN1–AHN4, 1996–2022). This resulted in <span class="inline-formula">∼59</span> GB raster layers in GeoTIFF format constituting ready-to-use multi-temporal data products of ecosystem structure at a national scale. For each AHN (Actueel Hoogtebestand Nederland) dataset, we generated 25 lidar-derived vegetation metrics at 10 m spatial resolution, representing vegetation height, vegetation cover, and vegetation structural variability, together with auxiliary data (<span class="inline-formula">∼12</span> GB) such as raster layers of point density; pulse density; flight line timestamp information; terrain and surface elevation; and masks of water areas, roads, buildings, power lines, and NA values (areas with no points available). The data enable an in-depth understanding of ecosystem structure at a fine resolution across the Netherlands and provide opportunities for exploring ecosystem structural dynamics over time. To illustrate the utility of these data products, we present ecological use cases that monitor forest structural change and analyse vegetation structure differences across various Natura 2000 habitat types, including dunes, marshes, grasslands, shrublands, and woodlands. The provided data products and the employed workflow can facilitate a wide use and uptake of ecosystem structure information in biodiversity and carbon modelling, conservation science, and ecosystem management. The full data products are publicly available on Zenodo (<a href="https://doi.org/10.5281/zenodo.13940846">https://doi.org/10.5281/zenodo.13940846</a>, Shi et al., 2025a).</p>https://essd.copernicus.org/articles/17/3641/2025/essd-17-3641-2025.pdf |
| spellingShingle | Y. Shi J. Wang W. D. Kissling Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands Earth System Science Data |
| title | Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands |
| title_full | Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands |
| title_fullStr | Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands |
| title_full_unstemmed | Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands |
| title_short | Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands |
| title_sort | multi temporal high resolution data products of ecosystem structure derived from country wide airborne laser scanning surveys of the netherlands |
| url | https://essd.copernicus.org/articles/17/3641/2025/essd-17-3641-2025.pdf |
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